AI RESEARCH
HPGN: Hybrid Priors-Guided Network for Compressed Low-Light Image Enhancement
arXiv CS.CV
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ArXi:2504.02373v3 Announce Type: replace-cross In practical applications, low-light images are often compressed for efficient storage and transmission. Most existing methods disregard compression artifacts removal or hardly establish a unified framework for joint task enhancement of low-light images with varying compression qualities. To address this problem, we propose an efficient hybrid priors-guided network (HPGN) that enhances compressed low-light images by integrating both compression and illumination priors.